The News: Pure Storage, in collaboration with NVIDIA, has announced several new proof-of-concept designs and reference architectures targeted at AI use cases. The reference architectures combine NVIDIA’s compute capabilities with storage from Pure to address the growing AI market and tackle vertical specific challenges. You can read more in the press release.
Pure Storage and NVIDIA Announce New Reference Architectures for AI
Analyst Take: The rapid growth of AI, and specifically generative AI, has challenged IT organizations to quickly deploy new AI workloads. This challenge is fueled both by the demanding resource requirements of AI, as well as general unfamiliarity with an emerging, and fast-moving technology. To assist organizations in quickly and successfully achieving their AI goals, Pure Storage and NVIDIA have announced a series of proof-of-concept designs and reference architectures focused on AI. The new announcement from Pure Storage includes the following features.
Certified NVIDIA OVX Server Storage Reference Architecture
Pure has achieved a NVIDIA OVX Server Storage certification, providing organizations with a validated reference design for deploying NVIDIA OVX systems for AI workloads. This recent certification follows Pure’s previous NVIDIA DGX BasePOD certification, providing additional options for organizations to deploy Pure and NVIDIA solutions for their AI needs. By providing these types of reference architectures, Pure and NVIDIA are providing a simplified, validated path for organizations to deploy the powerful compute and storage required for their AI workloads. As Pure continues to achieve NVIDIA certifications, such as this recent OVX certification, it provides greater flexibility for organizations with varying levels of AI requirements.
Retrieval Augmented Generation Pipeline for AI Inference
The generative AI models that are available today have demonstrated very powerful yet general capabilities. A key challenge for enterprise AI adoption is leveraging AI technology for industry or organization-specific use cases. To achieve these more context-specific results, AI models can be augmented with a process called retrieval augmented generation (RAG), in which an existing AI model is supplied with additional data during inferencing.
As organizations look to build beyond general use case AI applications toward solutions that are more accurate to their specific organization, RAG will be a key component. The RAG process, however, introduces an additional set of infrastructure requirements, as the process requires stored data to be quickly retrieved and processed during inferencing. To accelerate this process, Pure and NVIDIA have developed a reference RAG pipeline for large language models (LLMs) that utilizes NVIDIA GPU compute alongside Pure’s all flash storage.
Vertical RAG Development
To further assist organizations with RAG, Pure and NVIDIA are developing vertical-specific RAG designs that cater to specific industries. The first of these is a financial RAG, utilizing FinGPT, an open source financial model. They will follow this with additional solutions for healthcare and the public sector.
RAG will prove to be very valuable for AI solutions in these industries due to the accuracy compared with general, off-the-shelf LLMs. By creating these industry-specific solutions, Pure and NVIDIA are simplifying this process for organizations across several prominent sectors.
Expanded Investment in AI Partner Ecosystem
Along with the reference architectures and designs announced by Pure and NVIDIA, Pure has announced new investment into its AI partner ecosystem, including partnerships with ISVs including Run.AI and Weights and Biases. This announcement further showcases Pure’s ongoing activity in the AI space and its focus on working with new AI partners.
Final Thoughts
Providing integrated systems is not new. What is new is how infrastructure vendors are addressing the rapidly evolving AI market. And how customers are finding benefits in this approach. It is not just the combination of hardware but the software and ISVs that will expedite the deployments in the market.
Pure and NVIDIA are ultimately focused on helping organizations overcome their AI deployment challenges and simplifying the full AI application development. The newly announced designs bring the latest in technology and will help organizations accelerate their AI deployments not only with infrastructure challenges but also by simplifying some of the AI processes, such as RAG. Their continued focus on AI ISV partnerships will provide needed technology for AI practitioners.
The focus on RAG is a smart decision and it highlights Pure and NVIDIA’s understanding of new AI application requirements. Early generative AI adoption has mostly involved experimenting with off-the-shelf LLM models, but as organizations continue with their AI journey, they will require RAG solutions that can leverage private data and provide greater accuracy. The reference designs highlight Pure and NVIDIA’s ability to support these RAG workloads and accelerate AI development for their customers.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Mitch comes to The Futurum Group through the acquisition of the Evaluator Group and is focused on the fast-paced and rapidly evolving areas of cloud computing and data storage. Mitch joined Evaluator Group in 2019 as a Research Associate covering numerous storage technologies and emerging IT trends.
With a passion for all things tech, Mitch brings deep technical knowledge and insight to The Futurum Group’s research by highlighting the latest in data center and information management solutions. Mitch’s coverage has spanned topics including primary and secondary storage, private and public clouds, networking fabrics, and more. With ever changing data technologies and rapidly emerging trends in today’s digital world, Mitch provides valuable insights into the IT landscape for enterprises, IT professionals, and technology enthusiasts alike.
Now retired, Camberley brought over 25 years of executive experience leading sales and marketing teams at Fortune 500 firms. Before joining The Futurum Group, she led the Evaluator Group, an information technology analyst firm as Managing Director.
Her career spanned all elements of sales and marketing including a 360-degree view of addressing challenges and delivering solutions was achieved from crossing the boundary of sales and channel engagement with large enterprise vendors and her own 100-person IT services firm.
Camberley provided Global 250 startups with go-to-market strategies, creating a new market category “MAID” as Vice President of Marketing at COPAN and led a worldwide marketing team including channels as a VP at VERITAS. At GE Access, a $2B distribution company, she served as VP of a new division and succeeded in growing the company from $14 to $500 million and built a successful 100-person IT services firm. Camberley began her career at IBM in sales and management.
She holds a Bachelor of Science in International Business from California State University – Long Beach and executive certificates from Wellesley and Wharton School of Business.
